The detection of DDoS attacks is an important topic in the field of network security. The occurrence of software defined network (SDN) (Zhang et al., 2018) brings up some novel methods to this topic in which some deep learning algorithm is adopted to model the attack behavior based on collecting from the SDN controller. However, the existing methods such as neural network algorithm are not practical enough to be applied. In this paper, the SDN environment by mininet and floodlight (Ning et al., 2014) simulation platform is constructed, 6-tuple characteristic values of the switch flow table is extracted, and then DDoS attack model is built by combining the SVM classification algorithms. The experiments show that average accuracy rate of our method is 95.24% with a small amount of flow collecting. Our work is of good value for the detection of DDoS attack in SDN.
Purpose The purpose of this study is to examine the relationships among knowledge attributes (complexity and implicitness), interpersonal distrust, knowledge hiding (KH) and team efficacy and second, to explore a new dimension of KH. Design/methodology/approach Data for this research were collected from more than 940 employees working in manufacturing, information technology (IT), finance and the purification industry. Structural equation modeling was used to test hypothesized relationships. Findings First, the research confirmed the existence of bullying hiding behaviors in the knowledge economy era based on “knowledge power.” Second, the findings suggest that knowledge attributes are an important predictor of KH behaviors in organizations. The findings implicate the mediating effect of interpersonal distrust and the moderating role of team efficacy, while team efficacy negatively moderated the relationships between interpersonal distrust with evasive hiding and playing dumb, but positively moderated the relationship between interpersonal distrust with rationalized hiding and bullying hiding. Originality/value This is the first study to propose bullying hiding, a behavior that has emerged in organizational knowledge transfer, and it is more detrimental to knowledge sharing than other KH behaviors. The results of research on the different regulating effects of team efficacy on KH behaviors enrich the boundary conditions of KH research.
The issue of environmental protection and sustainable development is a key research focus across multiple fields. Employee green behavior is considered to be an important micro-activity to address this. Researchers in the field of organizational behavior and sustainable development have been focusing on the influencing factors of employee green behavior. However, few have explored the beneficial effects of employee green behavior on behavioral implementers. The objective of this study is to investigate the relationships among employee green behavior, self-esteem, perceived organizational support for employee environmental efforts, and employee well-being, and to explore a new dimension of employee green behavior. We empirically examined the underlying framework by conducting two surveys to collect data from 900 employees working in manufacturing, construction, and the service industry in China. We performed multilevel path analysis using SPSS and AMOS software, and confirmed that employee green behavior includes four dimensions: green learning, individual practice, influencing others, and organizational voices. Further, employee green behavior has a significant positive impact on self-esteem, which in turn is converted into employee well-being. Finally, perceived organizational support for employee environmental efforts not only positively moderated the relationship between employee green behavior and self-esteem, but was also confirmed as a moderated mediation model. This study enriches the current literature on the measurement framework and variables of employee green behavior.
Lifting and lowering a load on the ocean can be a dangerous task but can be made easy and safe by adopting heave compensation (HC) devices. The design and full-scale experimental results of a 3000-m semi-active heave compensation (AHC) system for a 200-T winch are presented in this paper. First, the design requirements are given and the semi-AHC mechanism is chosen. An integrated cylinder with one passive chamber and two active chambers is designed. Then, the capacities of the passive and active chambers are determined. The hydraulic and electrical systems and the control strategies are introduced subsequently. Finally, full-scale factory tests at different sinusoidal wave periods and amplitudes show that the semi-AHC system has a displacement compensation efficiency of 92.9% met the design requirements. In-depth power analysis further shows that the active and passive chambers contribute 20.5% and 72.4% displacement compensation efficiencies, respectively. The efficiency of the passive chamber consists with the 68%-80% passive compensation efficiency from Oceanworks Company and Rexroth Company.INDEX TERMS Integrated cylinder, passive heave, power analysis, semi-active heave compensation.
The problem of passivity analysis for discrete-time stochastic neural networks with time-varying delays is investigated in this paper. New delay-dependent passivity conditions are obtained in terms of linear matrix inequalities. Less conservative conditions are obtained by using integral inequalities to aid in the achievement of criteria ensuring the positiveness of the Lyapunov-Krasovskii functional. At last, numerical examples are given to show the effectiveness of the proposed method.
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